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Found 12 papers, 0 papers with code
The logic behind desirable sets of things, and its filter representation
We identify the logic behind the recent theory of coherent sets of desirable (sets of) things, which generalise desirable (sets of) gambles and coherent choice functions, and show that this identification allows us to establish various representation results for such coherent models in terms of simpler ones.
Decision-making with E-admissibility given a finite assessment of choices
Given information about which options a decision-maker definitely rejects from given finite sets of options, we study the implications for decision-making with E-admissibility.
On a notion of independence proposed by Teddy Seidenfeld
Teddy Seidenfeld has been arguing for quite a long time that binary preference models are not powerful enough to deal with a number of crucial aspects of imprecision and indeterminacy in uncertain inference and decision making.
Inference with Choice Functions Made Practical
We study how to infer new choices from previous choices in a conservative manner.
Coherent and Archimedean choice in general Banach spaces
I introduce and study a new notion of Archimedeanity for binary and non-binary choice between options that live in an abstract Banach space, through a very general class of choice models, called sets of desirable option sets.
Interpreting, axiomatising and representing coherent choice functions in terms of desirability
Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty.
A Desirability-Based Axiomatisation for Coherent Choice Functions
Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty.
Lexicographic choice functions
We investigate a generalisation of the coherent choice functions considered by Seidenfeld et al. (2010), by sticking to the convexity axiom but imposing no Archimedeanity condition.
Sensitivity analysis for finite Markov chains in discrete time
When the initial and transition probabilities of a finite Markov chain in discrete time are not well known, we should perform a sensitivity analysis.
Updating with incomplete observations
This is a fundamental problem, and of particular interest for Bayesian networks.
Irrelevant and independent natural extension for sets of desirable gambles
The independent natural extension of maximal coherent sets of desirable gambles allows us to define the strong product of sets of desirable gambles.
